code: def eval_func(model):
      metric = mx.gluon.metric.Accuracy()
      for x, label in val_data:
          output = model(x)
          metric.update(label, output)
      accuracy = metric.get()[1]
      return accuracy
  
file_path: mxnet/example/quantization_inc/resnet_tuning.py
imports: import logging
  import time
  import mxnet
  from mxnet.gluon.model_zoo.vision import resnet50_v2
  from mxnet.gluon.data.vision import transforms
  from mxnet.contrib.quantization import quantize_net
  import custom_strategy
  from neural_compressor.experimental import Quantization
label_desc: Use image node_id 2 for calling a global function with example usage: eval_func(model) and returns: accuracy